Jonathan Christopher Mattingly of Duke University has been selected to deliver the 2021 I.E. Block Community Lecture. He will be presenting the lecture at the SIAM Annual Meeting (AN21) which will be taking place virtually July 19 -23, 2021. Dr. Mattingly has been a proud and engaged member of SIAM for years. “SIAM was central to my scientific formation as an applied (stochastic) dynamicist,” Mattingly says. “I gave some of my first talks at SIAM Conferences and have been a regular at the SIAM Conference on Applications of Dynamical System for years as well as regularly attending many others. I feel strongly that the application of mathematics is important to our society and that the best applications breed great mathematics.” 

Dr. Mattingly grew up in Charlotte, North Carolina. He graduated from the NC School of Science and Mathematics and received a B.S. is Applied Mathematics with a concentration in physics from Yale University. After two years abroad with a year spent at ENS Lyon studying nonlinear and statistical physics on a Rotary Fellowship, he returned to the U.S. to attend Princeton University where he obtained a Ph.D. in Applied and Computational Mathematics in 1998 under the supervision of Yakov Sinai. After four years as a Szegö assistant professor at Stanford University and one year as a member of the IAS in Princeton, he moved to Duke in 2003, where he is currently James B. Duke Professor of Mathematics and a Professor of Statistical Science.

Since 2013 he has also been working to understand and quantify gerrymandering and its interaction with a region's geopolitical landscape. This has led him to testify in several court cases including Common Cause v. Rucho, which went all the way to the U.S. Supreme Court. He was also involved with a sequence of North Carolina state court cases which led to the NC congressional and both NC legislative maps being deemed unconstitutional and replaced for the 2020 elections. He was awarded the Defender of Freedom award by the Common Cause for his work on Quantifying Gerrymandering.

More info about the 2021 I. E. Block Community Lecture will be available in the coming months, but Dr. Mattingly gave us a preview of his work in gerrymandering that will be presented: The group at Duke has been centered on understanding and quantifying gerrymandering. The interaction between our laws and the geopolitical structure of our states is complicated enough that it resists simple reductive principles as a means of analysis. We have used computational sampling methods to create normative ensembles of maps that can be used as a baseline against which other maps can be compared. Central to this work has been a dialogue between lawyers and policy advocates and mathematicians. There are challenges in how to formulate the policy questions mathematically, in how to perform the needed collations in a computationally feasible way, and then in how to best transmit the results to empower policymakers, the courts, and the polis at large by increasing their understanding of the issues in play.

“It is important for people to understand gerrymandering and its effect on our election system,” he says. “My hope is to give a framework so that everyone can formulate the central issues in gerrymandering and be empowered to enter into the conversation both in the classroom and our political forums.”Dr. Mattingly is the recipient of an NSF CAREER award, a Presidential Early Career Award for Scientists and Engineers (PECASE), and a Sloan Foundation Faculty Fellowship. He is a fellow of the Institute for Mathematical Statistics (IMS) and the American Mathematics Society (AMS) and has served on the advisory boards for several NSF institutes. The I. E. Block Community Lecture is given each year at the SIAM Annual Meeting and is free and open to the public. Due to COVID-19, SIAM AN21 and the 2021 Block Lecture are happening virtually; the date and time will be announced in April.

Japanese researchers performed supercomputation of reaction kinetic information from first-principles calculations based on quantum mechanics, and developed methods and programs to carry out kinetic simulations without using experimental kinetic results. This method is expected to accelerate the search for various materials to achieve a carbon-free society.

Japanese researchers have developed a simulation method to theoretically estimate the performance of heterogeneous catalysts by combining first-principles calculation and kinetic calculation techniques. Up to now, simulation studies mainly focused on a single or limited number of reaction pathways, and it was difficult to estimate the efficiency of a catalytic reaction without experimental information.

Atsushi Ishikawa, Senior Researcher, Center for Green Research on Energy and Environmental Materials, National Institute for Materials Science (NIMS), performed computation of reaction kinetic information from first-principles calculations based on quantum mechanics, and developed methods and programs to carry out kinetic simulations without using experimental kinetic results. Then he applied the findings to the oxidative coupling of methane (OCM) reaction, which is an important process in the use of natural gas. He could successfully predict the yield of the products, such as ethane, without experimental information on the reaction kinetics. He also predicted changes in yield depending on the temperature and partial pressure, and the results reproduced faithfully the existing experimental results.

This research shows that the supercomputer simulation enables the forecasting of the conversion of reactants and the selectivity of products, even if experimental data are unavailable. The search for catalytic materials led by theory and calculation is expected to speed up. Furthermore, this method is highly versatile and can be applied not only to methane conversion catalysts but also to other catalyst systems such as automobile exhaust gas purification, carbon dioxide reduction, and hydrogen generation, and is expected to contribute to the realization of a carbon-free society.